Abstract: A data processing method is applied to processing of an image including a text, relates to the field of artificial intelligence, and includes: obtaining a first feature representation and a second feature representation, where the second feature representation is a text feature of a first text, and the first text is text content included in an image; and obtaining a third feature representation based on the first feature representation and the second feature representation by using a target encoder, where the third feature representation is used to execute a downstream task, and a similarity between an execution result and a corresponding label and a similarity between the first feature representation and the second feature representation are used to update an image encoder.

Abstract: A text data processing method, a neural-network training method, and related devices are provided. The methods may be applied to the text data processing field in the artificial intelligence field. The method includes: obtaining a to-be-processed text, where the to-be-processed text includes a plurality of characters; and processing the to-be-processed text by using a target model to obtain a prediction result, where the prediction result indicates to split the to-be-processed text into a plurality of target character sets, the prediction result further includes a plurality of first labels, one first label indicates semantics of one target character set, and the plurality of first labels are used to determine an intention of the to-be-processed text.